What would be a potential problem when treating discrete data as continuous?
- It can improve the accuracy of a machine learning model
- It can lead to inaccurate conclusions due to incorrect statistical analyses
- It can make the data cleaning process easier
- It can simplify the data visualization process
Treating discrete data as continuous can lead to inaccurate conclusions due to incorrect statistical analyses. For example, it can affect the choice of statistical tests or machine learning models, leading to potential misinterpretation of the data.
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